'insight' 검색 결과

Instrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web).

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Use when working with Azure App Insights — application Insights request performance, dependency tracking, availability tests, smart detection, and failure analysis via Azure CLI and Log Analytics queries.

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Signals scout that watches a PostHog project's most-viewed dashboards and insights for recent anomalies — sudden bursts, drops, flat-lines, and trend breaks at the daily or hourly level. It discovers what the team actually looks at (view counts, dashboard access), curates a durable watchlist in the scratchpad, and balances re-checking known high-value insights (exploit) against discovering new ones (explore) across runs, since no single run can cover a busy project. Anomalies are scored by robust deviation from each insight's own seasonality-matched baseline; it emits a finding only when a move clears the confidence bar, otherwise it updates the baseline memory and closes out empty. Self-contained peer in the signals-scout-* fleet.

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Focused Signals scout for finding observability gaps in PostHog itself — significant event volumes the team isn't tracking, custom events with no insight or dashboard coverage, insights pointing at events that have stopped firing, dashboards missing related context, critical events with no alerts. Watches the event-stream-vs-saved- inventory delta as the team's product evolves and emits findings recommending new insights, dashboard additions, or alerts when gaps clear the confidence bar. Self-contained peer in the signals-scout-* fleet — no dependencies on other skills.

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Extract AI customer insights. TRIGGERS - Use when user needs help with ai-customer-insights related tasks.

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Extract actionable insights from blog posts, web articles, and practitioner content - assess credibility, run security checks, and either improve existing skills or apply to the current project. Load when the user asks to learn from an article, extract insights from a blog post, apply a practitioner's findings, or process engineering blog content. Also triggers on "learn from this article", "learn from this blog post", "extract insights from this post", "what can we learn from this article", "apply this article", or when the user links to a blog, Medium, Substack, dev.to, or engineering blog post.

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Use for insight, reframing, contradiction, impasse, and anomaly-driven problem solving when execution effort no longer helps. NOT for routine optimization, error correction, or well-specified tasks with known solution paths.

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Erstellt aus einem YouTube-Video- oder Kanal-Link eine faktenbelegte Insight-Card (Video- und Kanal-Stats) per Websuche. Nutzen, wenn jemand Stats/Analyse zu einem YouTube-Link will. Gibt nur belegte Zahlen aus, nie geratene.

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여러 소셜 플랫폼의 지표를 하나의 HTML 분석 대시보드로 만듭니다. 그래프 상세 정보와 기간 비교, 밝고 어두운 테마 전환을 제공하고 디자인 지침을 반영합니다.

• 여러 소셜 플랫폼 지표를 한곳에서 확인
• 그래프에서 선택한 기간 비교
• 그래프의 각 지점과 분석 내용 확인

Review and rewrite Twitter drafts using insights from its open-source recommendation algorithm. The skill examines audience fit, replies, sharing, and negative reactions, then explains suggested edits and ways to refine your content strategy.

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• Revise a draft to encourage replies and sharing
• Explore why a tweet received little engagement
• Refine a posting strategy for a specific community

Analyze meeting transcripts to understand speaking habits, interruptions, conflict avoidance, and listening patterns. Get concrete examples and practical suggestions, then compare meetings over time to review changes in communication and facilitation.

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• Identify moments of conflict avoidance
• Review speaking share, interruptions, and filler words
• Assess meeting facilitation and participation

Measure how quickly a webpage updates after user interactions using INP, a responsiveness metric. Identify confirmed bottlenecks and improve event handlers, split long tasks, or move heavy computation to web workers.

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• Investigating slow responses to clicks and other interactions
• Reviewing event handlers and long tasks using measurements
• Considering web workers for heavy computation

Audit how quickly a page shows its first text or image. Use performance measurements to identify blocking resources, slow server responses, and rendering delays, then recommend changes tied to the confirmed bottlenecks.

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• Investigating slow initial page display
• Finding CSS and JavaScript that delay rendering
• Reviewing loading performance with measurements

Have agents with different roles challenge a proposed approach, exposing weak assumptions, missed interactions, and unnecessary complexity. Surviving findings go to a dedicated planning agent, which produces sequenced tasks with explicit success criteria.

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• Checking assumptions before committing to a plan
• Finding integration risks and overlooked edge cases
• Challenging unnecessary complexity in a design

Develop Azure Functions with guidance for .NET, Python, and Node.js. Covers asynchronous processing, Durable Functions for coordinating tasks, startup delay optimization, and production concerns such as timeouts, HTTP client reuse, and monitoring configuration.

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• Choose an execution model for a new .NET function
• Coordinate asynchronous tasks with Durable Functions
• Review startup delays and timeout settings

Restructure raw article text stored in gbrain into summaries, exact quotes, key insights, and links to related pages. Preserve the original text and connect the article's significance to projects and interests already recorded in gbrain.

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• Organizing saved articles into readable notes
• Collecting exact quotes for essays
• Connecting articles to current projects

Add persistent memory to NanoClaw agents using the default Claude provider. With mnemon installed in the container, agents retrieve relevant context before responding and save new insights after each turn, retaining memory across container restarts.

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• Recalling earlier conversations in a new session
• Keeping agent memory across container restarts
• Checking memory hooks and storage settings

Turn survey responses, interviews, and other research data into three distinct user personas. Each profile explains the outcome users seek, their main difficulties, desired benefits, an unexpected behavioral insight, and how well the product meets their needs.

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• Creating three personas from survey responses
• Grouping interview findings by user goals and behavior
• Comparing user needs to guide product decisions

Extract useful ideas from videos, podcasts, interviews, and articles, organized into sections tailored to the content. Choose from five depth levels, preserving surprising claims and, at fuller levels, getting essential takeaways and references to explore.

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• Extract key insights from a YouTube interview
• Review a podcast at a chosen level of detail
• Organize useful ideas from an article

Apply over 240 reusable prompt templates to summarize content, extract insights, improve writing, review code, or analyze security threats. It reads each template directly and returns results in the format defined for that task.

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• Extract ideas and insights from an article
• Create a concise five-sentence summary
• Improve writing or review code with a selected template

Analyze meeting transcripts to understand speaking habits, interruptions, conflict avoidance, and listening patterns. Get specific examples with timestamps and practical suggestions, then compare meetings over time to track changes in communication and facilitation.

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• Find moments when difficult conversations were avoided
• Review speaking time and interruptions
• Assess facilitation in team meetings

Identify which Convex functions drive spending by combining data read per call with call volume. Use deployment evidence or query structure to explain how costs grow with usage and data size, then suggest the cheapest fix for each driver.

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• Find functions that drive Convex spending
• Assess cost growth as data and traffic increase
• Estimate future cost drivers before traffic arrives

Combine Convex authorization, code quality, performance, and failure audits into one readiness report. It removes duplicate findings, scores confirmed issues with a stated formula, and orders the fixes while clearly identifying checks that could not run.

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• Reviewing a Convex app before launch
• Combining audit findings into one report
• Prioritizing authorization and performance fixes

Review 72 hours of Convex deployment health events and trace read limits or conflicting writes to the responsible code. Receive prioritized performance, cost, and reliability findings with runtime evidence, source locations, and concrete fixes.

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• Investigating read limits and large table scans
• Tracing conflicting writes to shared records
• Reviewing deployment performance and cost issues